Senior Game Engineer, Genai - Games

Netflix Netflix · Big Tech · Los Angeles, CA +2 · Netflix Games Studio

Senior Game Engineer at Netflix focused on integrating Generative AI into gameplay systems to create dynamic and player-responsive experiences. The role involves working with game designers, implementing GenAI features, integrating them into core game systems, developing safety and quality guardrails, and using GenAI for rapid iteration and tool building. Requires strong game engineering experience and applied GenAI skills with LLMs or Diffusion models.

What you'd actually do

  1. Design-Led Engineering: Work elbow-to-elbow with Game Designers to prototype and ship AI-augmented gameplay.
  2. Player-Centric AI: Implement GenAI features that directly enhance the player experience, ensuring that AI-generated content feels intentional, high-quality, and most importantly, fun.
  3. Core Systems Integration: Architect how GenAI hooks into core game systems (AI behavior trees, narrative engines, and world-building tools) to ensure seamless, low-latency performance.
  4. Guardrails & UX: Develop the "logic layer" that sits between raw AI outputs and the player, ensuring content remains on-theme, safe, and balanced within the game's mechanics.
  5. Rapid Gameplay Iteration: Use GenAI to accelerate the "find the fun" phase of development, building internal tools that allow for faster level blocking, asset variation, and playtesting loops.

Skills

Required

  • 5+ years of professional experience in game development
  • Deep understanding of game architecture, player controllers, and real-time systems
  • Proven experience using LLMs or Diffusion models to solve specific product problems
  • Expert-level C++ or C# (Unity/Unreal)
  • Grasp of Python for tooling and data pipelines

Nice to have

  • Prompting LLMs
  • Fine-tuning LLMs
  • Chaining LLMs

What the JD emphasized

  • Proven experience using LLMs or Diffusion models to solve specific product problems
  • You know how to prompt, fine-tune, and chain models to get predictable results in an unpredictable game world
  • Expert-level C++ or C# (Unity/Unreal) and a grasp of Python for tooling and data pipelines

Other signals

  • Leverage Generative AI to break traditional scripted boundaries
  • Implement GenAI features that directly enhance the player experience
  • Architect how GenAI hooks into core game systems
  • Develop the "logic layer" that sits between raw AI outputs and the player
  • Use GenAI to accelerate the "find the fun" phase of development